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474 results on '"Hong-na An"'

1. Cortical superficial siderosis, hematoma volume, and outcomes after intracerebral hemorrhage: a mediation analysis

Author

Yu-jia Jin, Jia-wen Li, Jian Wu, Yu-hui Huang, Kai-cheng Yang, Hong-na An, Chang-zheng Yuan, Feng Gao, and Lu-sha Tong

Subjects
cSS, ICH volume and outcome, mediation analysis, prospective studies, cerebral hemorrhage, hematoma, Neurology. Diseases of the nervous system, RC346-429
Abstract

BackgroundPrevious studies have shown that cortical superficial siderosis (cSS) can increase hematoma volume and predict poor outcomes following primary intracerebral hemorrhage (ICH).ObjectiveWe aimed to determine whether a large hematoma volume was the essential factor contributing to worse outcomes of cSS.MethodsPatients with spontaneous ICH underwent a CT scan within 48 h after ictus. Evaluation of cSS was performed using magnetic resonance imaging (MRI) within 7 days. The 90-day outcome was assessed using the modified Rankin Scale (mRS). In addition, we investigated the correlation between cSS, hematoma volume, and 90-day outcomes using multivariate regression and mediation analyses.ResultsAmong the 673 patients with ICH [mean (SD) age, 61 (13) years; 237 female subjects (35.2%); median (IQR) hematoma volume, 9.0 (3.0–17.6) ml], 131 (19.5%) had cSS. There was an association between cSS and larger hematoma volume (β = 4.449, 95% CI 1.890–7.009, p < 0.001) independent of hematoma location and was also related to worse 90-day mRS (β = 0.333, 95% CI 0.008–0.659, p = 0.045) in multivariable regression. In addition, mediation analyses revealed that hematoma volume was an essential factor mediating the effect of cSS on unfavorable 90-day outcomes (proportion mediated:66.04%, p = 0.01).ConclusionLarge hematoma volume was the major charge of directing cSS to worse outcomes in patients with mild to moderate ICH, and cSS was related to a larger hematoma in both lobar and non-lobar areas.Clinical trial registrationhttps://clinicaltrials.gov/ct2/show/NCT04803292, identifier: NCT04803292.

Published
2023
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2. The large-scale modular BGO detection array (LAMBDA) design and test

Author

Sheng, Yao-De, Song, Lu-Yang, Su, Jun, Jin, Shi-Lun, Lu, Fei, Shen, Yang-Ping, Chen, Jun-Feng, Zhang, Li-Yong, He, Jian-Jun, Li, Xin-Yue, Liu, Hong-Na, Zhang, Feng-Shou, Qiu, Meng-Lin, Lin, Shen, Zhang, Hao, Wang, Luo-Huan, Li, Zi-Ming, Chen, Yin-Ji, Jiang, Xin-Zhi, Chen, Xin, Shen, Zhi-Lin, Liu, Feng-Cheng, Qin, Zhi-Wei, Wang, Lin, Huang, Yi-Tong, Li, Xiang, Chen, Si-Ze, Wang, You-Bao, Li, Zhi-Hong, Guo, Bing, and Liu, Wei-Ping

Published
2024
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3. Neuropeptide Y in first-episode schizophrenia: is there any sex differences in the pathogeneses of schizophrenia?

Author

Jia-Qi Song, Wen Xin, Jian-Jin Yu, Qing Zhao, Hong-Na Li, and Da-Chun Chen

Subjects
neuropeptide Y, schizophrenia, sex difference, risperidone, PANSS, cohort study, Psychiatry, RC435-571
Abstract

ObjectiveThis study investigated relationships between Neuropeptide Y levels and severity of psychiatric symptoms in first-episode schizophrenia patients, and explore the sexual heterogeneity in them.MethodsWe recruited 115 first-episode schizophrenia patients and 58 matched healthy controls, and measured serum Neuropeptide Y levels of them at baseline and again after 10 weeks of risperidone treatment in patient group. Patients were also evaluated with the Positive and Negative Symptoms Scale (PANSS) to reveal the severity of symptoms.Results95 patients completed the whole experiment. We find that mean Neuropeptide Y levels at baseline were significantly higher in patients than in controls (p

Published
2024
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45. Relation extraction using large language models: a case study on acupuncture point locations.

Author

Li, Yiming, Peng, Xueqing, Li, Jianfu, Zuo, Xu, Peng, Suyuan, Pei, Donghong, Tao, Cui, Xu, Hua, and Hong, Na

Abstract

Objective In acupuncture therapy, the accurate location of acupoints is essential for its effectiveness. The advanced language understanding capabilities of large language models (LLMs) like Generative Pre-trained Transformers (GPTs) and Llama present a significant opportunity for extracting relations related to acupoint locations from textual knowledge sources. This study aims to explore the performance of LLMs in extracting acupoint-related location relations and assess the impact of fine-tuning on GPT's performance. Materials and Methods We utilized the World Health Organization Standard Acupuncture Point Locations in the Western Pacific Region (WHO Standard) as our corpus, which consists of descriptions of 361 acupoints. Five types of relations ("direction_of", "distance_of", "part_of", "near_acupoint", and "located_near") (n  = 3174) between acupoints were annotated. Four models were compared: pre-trained GPT-3.5, fine-tuned GPT-3.5, pre-trained GPT-4, as well as pretrained Llama 3. Performance metrics included micro-average exact match precision, recall, and F1 scores. Results Our results demonstrate that fine-tuned GPT-3.5 consistently outperformed other models in F1 scores across all relation types. Overall, it achieved the highest micro-average F1 score of 0.92. Discussion The superior performance of the fine-tuned GPT-3.5 model, as shown by its F1 scores, underscores the importance of domain-specific fine-tuning in enhancing relation extraction capabilities for acupuncture-related tasks. In light of the findings from this study, it offers valuable insights into leveraging LLMs for developing clinical decision support and creating educational modules in acupuncture. Conclusion This study underscores the effectiveness of LLMs like GPT and Llama in extracting relations related to acupoint locations, with implications for accurately modeling acupuncture knowledge and promoting standard implementation in acupuncture training and practice. The findings also contribute to advancing informatics applications in traditional and complementary medicine, showcasing the potential of LLMs in natural language processing. [ABSTRACT FROM AUTHOR]

Published
2024
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